Suboptimal decision making and interpersonal problems in ADHD: longitudinal evidence from a laboratory task

Over half of children with Attention-Deficit/Hyperactivity Disorder (ADHD) display interpersonal and social problems. Several lines of research suggest that suboptimal decision making, the ability to adjust choices to different risk-varying options, influences poorer choices made in social interactions. We thus measured decision making and its prediction of social problems longitudinally with the Cambridge Gambling Task in children with ADHD over four years. Children with ADHD had shown suboptimal decision making driven mainly by delay aversion at baseline and we expected this to be a stabile trait which would predict greater parent-reported social problems. From the baseline assessment (n = 70), 67% participated at the follow-up assessment, 21 from the ADHD group and 26 from the typically developing group. The mean age at the follow-up was 14.5 years old. The results confirmed our expectations that suboptimal decision making was a stabile trait in children and adolescents with ADHD. Although delay aversion did not differ from controls at follow-up it still proved to be the main longitudinal predictor for greater social problems. Our findings indicate that impulsivity in social interactions may be due to a motivational deficit in youth with ADHD.

Description of a clinical intervention among patients admitted to the medium secure forensic psychiatric services in Central Denmark Region

Introduction

Patients with schizophrenia suffer from increased mortality rates equivalent to 15-20 years shorter life expectancy. Up to 60% of this excess mortality can be explained by preventable, somatic conditions like cardiovascular, metabolic, and respiratory comorbidities. As forensic psychiatric (FP) patients often experience the triple stigmatization of mental illness, substance misuse and criminal conviction, the risk of suboptimal diagnosis and treatment may be high. Although benefits from the addition of general practitioner (GP) services to non-FP wards have been shown elsewhere, this cross-sectoral approach has never been attempted in a Danish FP ward.

Objectives

One purpose of this project is to evaluate the associations between self-reported quality of life and objective measures of somatic health.

Methods

A clinical intervention in which a GP consults patients in all medium secure wards in the Central Denmark Region (N=72). The consultation includes a physical examination, medication review, and evaluation of blood samples. Data is collected from: electronic patient files and questionnaires regarding quality of life (SF-12), lifestyle, and attitude towards GP services.

Results

The population will be described in regards to socio-demographic, clinical, and forensic characteristics. Associations will be made between quality of life (SF-12), metabolic syndrome, blood markers, and heart-SCORE risk. Risk profiles for endocrinologic and coronary illness will be examined.

Conclusions

Results may guide future health interventions and will be used as a basis for adjustments to the current project.

Disclosure

No significant relationships.

Tidier. e-sport; a recovery oriented intervention in forensic psychiatry

Introduction

Recently video gaming, have attracted considerable attention for its possible beneficial therapeutic effects, the possibility for testing behavior in safe artificial environments and as a tool for professionals and patients to build specific competencies for the everyday life. Also, a substantial amount of research suggests that videogaming might improve the participants social and cognitive skills and emotional regulation. There is little or no evidence that videogaming increases long term aggression or leads to physical aggression. At a medium secure forensic psychiatric in-patient ward, the patients and staff engage in weekly E – Sport sessions (primarily counterstrike) to further the recovery process.

Objectives

To provide a standardized description of how E-sport is organized and used in the recovery process among forensic psychiatric patients.

Methods

The Template for Intervention Description and Replication (TIDieR) checklist and guide is widely used to in health research to describe interventions in clinical trials and other health research contexts. By use of TIDieR we describe a newly developed E-sport intervention, in which staff members and patients in a medium secure forensic psychiatric ward engage in weekly E-Sport sessions (primarily counterstrike) to improve patient–staff relationship.

Results

The E-sport intervention is detailed by use of the 12 TIDieR items and practical experiences and insights will be described.

Conclusions

This standardized and detailed description of how is used in a recovery-oriented process in forensic psychiatry can be used for future studies that wishes to implement the intervention or for research studies replicating the treatment.

Conflict of interest

No significant relationships.

Modernized architecture may reduce coercion

Introduction

Prevention and treatment of aggression in psychiatric hospitals is achieved through appropriate medical treatment, professional skills, and optimized physical environment and architecture. Coercive measures are used as a last resort. In 2018 Aarhus University Hospital Psychiatry moved from 19th-century asylum buildings to a newly built modern psychiatric hospital. Advances within psychiatric care have rendered the old psychiatric asylum hospitals inadequate for modern treatment of mental disorders.

Objectives

To examine if relocating from a psychiatric hospital, dating from 19th century to a new, modern psychiatric hospital decreased the use of coercive measures.

Methods

This is a retrospective longitudinal study, with a follow-up from 2017 to 2019. We use two designs; 1) a pre-post analysis of the use of coercive measures at Aarhus University Hospital Psychiatry before and after the relocation and 2) a case-control analysis of Aarhus University Hospital Psychiatry and the other psychiatric hospitals in the Central Region. Data will be analyzed in STATA using an interrupted time-series analysis or similar method. Additionally case-mix and sensitivity analysis will be performed.

Results

Preliminary results show a 45% decrease in the total number of coercive measures and a 52% decrease in the use of mechanical restraint. The reduction that may reasonably be attributed to the relocation is still to be determined and will be presented at the congress.

Conclusions

The study may illuminate how future development and planning of psychiatric facilities might improve psychiatric treatment and increase the understanding of how structural changes might contribute the prevention of the use of coercive measures.

Disclosure

No significant relationships.

Robust parametric modeling of Alzheimer's disease progression

Quantitative characterization of disease progression using longitudinal data can provide long-term predictions for the pathological stages of individuals. This work studies the robust modeling of Alzheimer's disease progression using parametric methods. The proposed method linearly maps the individual's age to a disease progression score (DPS) and jointly fits constrained generalized logistic functions to the longitudinal dynamics of biomarkers as functions of the DPS using M-estimation. Robustness of the estimates is quantified using bootstrapping via Monte Carlo resampling, and the estimated inflection points of the fitted functions are used to temporally order the modeled biomarkers in the disease course. Kernel density estimation is applied to the obtained DPSs for clinical status classification using a Bayesian classifier. Different M-estimators and logistic functions, including a novel type proposed in this study, called modified Stannard, are evaluated on the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) for robust modeling of volumetric magnetic resonance imaging (MRI) and positron emission tomography (PET) biomarkers, cerebrospinal fluid (CSF) measurements, as well as cognitive tests. The results show that the modified Stannard function fitted using the logistic loss achieves the best modeling performance with an average normalized mean absolute error (NMAE) of 0.991 across all biomarkers and bootstraps. Applied to the ADNI test set, this model achieves a multiclass area under the ROC curve (AUC) of 0.934 in clinical status classification. The obtained results for the proposed model outperform almost all state-of-the-art results in predicting biomarker values and classifying clinical status. Finally, the experiments show that the proposed model, trained using abundant ADNI data, generalizes well to data from the National Alzheimer's Coordinating Center (NACC) with an average NMAE of 1.182 and a multiclass AUC of 0.929.

Inflammatory pathway analytes predicting rapid cognitive decline in MCI stage of Alzheimer's disease

OBJECTIVE

To determine the inflammatory analytes that predict clinical progression and evaluate their performance against biomarkers of neurodegeneration.

METHODS

A longitudinal study of MCI-AD patients in a Discovery cohort over 15 months, with replication in the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort over 36 months. Fifty-three inflammatory analytes were measured in the CSF and plasma with a RBM multiplex analyte platform. Inflammatory analytes that predict clinical progression on Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) and Mini Mental State Exam scores were assessed in multivariate regression models. To provide context, key analyte results in ADNI were compared against biomarkers of neurodegeneration, hippocampal volume, and CSF neurofilament light (NfL), in receiver operating characteristic (ROC) analyses evaluating highest quartile of CDR-SB change over two years (≥3 points).

RESULTS

Cerebrospinal fluid inflammatory analytes in relation to cognitive decline were best described by gene ontology terms, natural killer cell chemotaxis, and endothelial cell apoptotic process and in plasma, extracellular matrix organization, blood coagulation, and fibrin clot formation described the analytes. CSF CCL2 was most robust in predicting rate of cognitive change and analytes that correlated to CCL2 suggest IL-10 pathway dysregulation. The ROC curves for ≥3 points change in CDR-SB over 2 years when comparing baseline hippocampal volume, CSF NfL, and CCL2 were not significantly different.

INTERPRETATION

Baseline levels of immune cell chemotactic cytokine CCL2 in the CSF and IL-10 pathway dysregulation impact longitudinal cognitive and functional decline in MCI-AD. CCL2's utility appears comparable to biomarkers of neurodegeneration in predicting rapid decline.

Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning

Supervised learning algorithms trained on medical images will often fail to generalize across changes in acquisition parameters. Recent work in domain adaptation addresses this challenge and successfully leverages labeled data in a source domain to perform well on an unlabeled target domain. Inspired by recent work in semi-supervised learning we introduce a novel method to adapt from one source domain to n target domains (as long as there is paired data covering all domains). Our multi-domain adaptation method utilises a consistency loss combined with adversarial learning. We provide results on white matter lesion hyperintensity segmentation from brain MRIs using the MICCAI 2017 challenge data as the source domain and two target domains. The proposed method significantly outperforms other domain adaptation baselines.

A psychophysiological investigation of the interplay between orienting and executive control during stimulus conflict: A heart rate variability study

BACKGROUND

It has been hypothesized that resting state cardiac vagal activity (CVA) - an indicator of parasympathetic nervous system activity - is a specific psychophysiological marker of executive control function. Here, we propose an alternative hypothesis - that CVA is associated with early stage attention orientation, promoting the flexible uptake of new information, on which the later operation of such executive control functions depends. We therefore predicted that CVA would predict the interaction between orienting and executive control. This was tested using the revised version of the Attention Network Test (ANT-R) that was developed to distinguish between orienting and executive attention during a stimulus conflict task.

METHODS

Healthy adults (N = 48) performed the ANT-R and their resting CVA was measured over a 5 min period using ECG recordings.

RESULTS

Multiple regression analyses indicated that, when other factors were controlled for, CVA was more strongly associated with the interaction between the orienting and executive control terms than with either factor individually.

CONCLUSION

Higher levels of CVA are specifically implicated in the modulation of executive control by intrinsic orientation operating at early stages of conflict detection. These initial findings of higher CVA on orienting attention in conflict detection need to be replicated in larger samples.

Subclinical depressive symptoms during late midlife and structural brain alterations: A longitudinal study of Danish men born in 1953

We explored whether depressive symptoms measured three times during midlife were associated with structural brain alterations quantified using magnetic resonance imaging measurements of volume, cortical thickness, and intensity texture. In 192 men born in 1953 with depressive symptoms measured at age 51, 56, and 59 years, magnetic resonance imaging was performed at age 59. All data processing was performed using the Freesurfer software package except for the texture-scores that were computed using in-house software. Structural brain alterations and associations between depressive symptoms and brain structure outcomes were tested using Pearson's correlation, t test, and linear regression. Depressive symptoms at age 51 showed clear inverse correlations with total gray matter, pallidum, and hippocampal volume with the strongest estimate for hippocampal volume (r = -.22, p < .01). After exclusion of men (n = 3) with scores in the range of clinical depression the inverse correlation between depressive symptoms and hippocampal volume became insignificant (r = -13, p = .08). Depressive symptoms at age 59 correlated positively with hippocampal and amygdala texture-potential early markers of atrophy. Inverse relations with total gray matter and pallidum volumes lost significance when the analysis was adjusted for intracranial volume. In men, depressive symptoms at age 51 were associated with a reduced volume of the hippocampus at age 59 independent of later symptoms. Amygdala and hippocampal textures might be the early markers for brain alterations associated with depression in midlife.

Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry

This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI) biomarker that combines several individual MRI biomarkers (cortical thickness measurements, volumetric measurements, hippocampal shape, and hippocampal texture). The method was developed, trained, and evaluated using two publicly available reference datasets: a standardized dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the imaging arm of the Australian Imaging Biomarkers and Lifestyle flagship study of ageing (AIBL). In addition, the method was evaluated by participation in the Computer-Aided Diagnosis of Dementia (CADDementia) challenge. Cross-validation using ADNI and AIBL data resulted in a multi-class classification accuracy of 62.7% for the discrimination of healthy normal controls (NC), subjects with mild cognitive impairment (MCI), and patients with Alzheimer's disease (AD). This performance generalized to the CADDementia challenge where the method, trained using the ADNI and AIBL data, achieved a classification accuracy 63.0%. The obtained classification accuracy resulted in a first place in the challenge, and the method was significantly better (McNemar's test) than the bottom 24 methods out of the total of 29 methods contributed by 15 different teams in the challenge. The method was further investigated with learning curve and feature selection experiments using ADNI and AIBL data. The learning curve experiments suggested that neither more training data nor a more complex classifier would have improved the obtained results. The feature selection experiment showed that both common and uncommon individual MRI biomarkers contributed to the performance; hippocampal volume, ventricular volume, hippocampal texture, and parietal lobe thickness were the most important. This study highlights the need for both subtle, localized measurements and global measurements in order to discriminate NC, MCI, and AD simultaneously based on a single structural MRI scan. It is likely that additional non-structural MRI features are needed to further improve the obtained performance, especially to improve the discrimination between NC and MCI.

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The algorithm that won the CADDementia challenge is described and analyzed.

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Evaluation on data from ADNI, AIBL and the CADDementia challenge.

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Hippocampal texture is shown to be an important feature in the algorithm.

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Structural MRI intensity variations may include so far unused information.

•

It is conjectured that additional features are needed in order to improve diagnostic performance.

Systemic and Pulmonary Haemodynamic Effects of Intravenous Infusion of Non-Ionic Isoosmolar Dimeric Contrast Media

The systemic and pulmonary haemodynamic effects of i.v. infusion (1 ml/s) of high doses (4 ml/kg) of 2 non-ionic, isoosmolar dimeric contrast media (CM) were investigated in 17 female pigs. The 2 CM were iodixanol and iotrolan. Both CM induced a significant increase of the following parameters: mean arterial, mean right atrial, mean pulmonary arterial, mean pulmonary arterial occlusion pressure, cardiac output, stroke volume, and diuresis. The plasma concentration of atrial natriuretic peptide was significantly increased following infusion of the 2 CM. A significant decrease was seen in the systemic and pulmonary vascular resistance.

Amplitude variability over trials in hemodynamic responses in adolescents with ADHD: The role of the anterior default mode network and the non-specific role of the striatum

It has been suggested that intra-individual variability (IIV) in performance on attention and other cognitive tasks might be a cognitive endophenotype in individuals with ADHD. Despite robust IIV findings in behavioral data, only sparse data exist on how what type of brain dysfunction underlies variable response times. In this study, we asked whether ADHD IIV in reaction time on a commonly-used test of attention might be related to variation in hemodynamic responses (HRs) observed trial-to-trial. Based on previous studies linking IIV to regions within the “default mode” network (DMN), we predicted that adolescents with ADHD would have higher HR variability in the DMN compared with controls, and this in turn would be related to behavioral IIV. We also explored the influence of social anxiety on HR variability in ADHD as means to test whether higher arousal associated with high trait anxiety would affect the neural abnormalities. We assessed single-trial variability of HRs, estimated from fMRI event-related responses elicited during an auditory oddball paradigm in adolescents with ADHD and healthy controls (11–18 years old; N = 46). Adolescents with ADHD had higher HR variability compared with controls in anterior regions of the DMN. This effect was specific to ADHD and not associated with traits of age, IQ and anxiety. However, an ADHD effect of higher HR variability also appeared in a basal ganglia network, but for these brain regions the relationships of HR variability and social anxiety levels were more complex. Performance IIV correlated significantly with variability of HRs in both networks. These results suggest that assessment of trial-to-trial HR variability in ADHD provides information beyond that detectable through analysis of behavioral data and average brain activation levels, revealing specific neural correlates of a possible ADHD IIV endophenotype.

•

We studied if the behavioral variability in ADHD is also found on a neuronal level.

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Independent component analysis was combined with BOLD amplitude variability.

•

Adolescents with ADHD had higher amplitude variability than healthy controls.

•

Higher amplitude variability was shown in an anterior default mode network.

•

Social anxiety in ADHD associated with high amplitude variability in the striatum

Deformation-based atrophy computation by surface propagation and its application to Alzheimer's disease

Obtaining regional volume changes from a deformation field is more precise when using simplex counting (SC) compared with Jacobian integration (JI) due to the numerics involved in the latter. Although SC has been proposed before, numerical properties underpinning the method and a thorough evaluation of the method against JI is missing in the literature. The contributions of this paper are: (a) we propose surface propagation (SP)-a simplification to SC that significantly reduces its computational complexity; (b) we will derive the orders of approximation of SP which can also be extended to SC. In the experiments, we will begin by empirically showing that SP is indeed nearly identical to SC, and that both methods are more stable than JI in presence of moderate to large deformation noise. Since SC and SP are identical, we consider SP as a representative of both the methods for a practical evaluation against JI. In a real application on Alzheimer's disease neuroimaging initiative data, we show the following: (a) SP produces whole brain and medial temporal lobe atrophy numbers that are significantly better than JI at separating between normal controls and Alzheimer's disease patients; (b) SP produces disease group atrophy differences comparable to or better than those obtained using FreeSurfer, demonstrating the validity of the obtained clinical results. Finally, in a reproducibility study, we show that the voxel-wise application of SP yields significantly lower variance when compared to JI.

Early detection of Alzheimer's disease using MRI hippocampal texture

Cognitive impairment in patients with Alzheimer's disease (AD) is associated with reduction in hippocampal volume in magnetic resonance imaging (MRI). However, it is unknown whether hippocampal texture changes in persons with mild cognitive impairment (MCI) that does not have a change in hippocampal volume. We tested the hypothesis that hippocampal texture has association to early cognitive loss beyond that of volumetric changes. The texture marker was trained and evaluated using T1-weighted MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, and subsequently applied to score independent data sets from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) and the Metropolit 1953 Danish Male Birth Cohort (Metropolit). Hippocampal texture was superior to volume reduction as predictor of MCI-to-AD conversion in ADNI (area under the receiver operating characteristic curve [AUC] 0.74 vs. 0.67; DeLong test, p = 0.005), and provided even better prognostic results in AIBL (AUC 0.83). Hippocampal texture, but not volume, correlated with Addenbrooke's cognitive examination score (Pearson correlation, r = -0.25, p < 0.001) in the Metropolit cohort. The hippocampal texture marker correlated with hippocampal glucose metabolism as indicated by fluorodeoxyglucose-positron emission tomography (Pearson correlation, r = -0.57, p < 0.001). Texture statistics remained significant after adjustment for volume in all cases, and the combination of texture and volume did not improve diagnostic or prognostic AUCs significantly. Our study highlights the presence of hippocampal texture abnormalities in MCI, and the possibility that texture may serve as a prognostic neuroimaging biomarker of early cognitive impairment.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI

BACKGROUND

Alzheimer's disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects.

METHODS

A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume.

RESULTS

We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period.

CONCLUSION

Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.

Remote Ischemic Perconditioning in Thrombolysed Stroke Patients: Randomized Study of Activating Endogenous Neuroprotection – Design and MRI Measurements

Background

Intravenous administration of alteplase is the only approved treatment for acute ischemic stroke. Despite the effectiveness of this treatment, 50% of patients suffer chronic neurological disability, which may in part be caused by ischemia-reperfusion injury. Remote ischemic perconditioning, performed as a transient ischemic stimulus by blood-pressure cuff inflation to an extremity, has proven effective in attenuating ischemia-reperfusion injury in animal models of stroke. Remote ischemic perconditioning increases myocardial salvage in patients undergoing acute revascularization for acute myocardial infarction. To clarify whether a similar benefit can be obtained in patients undergoing thrombolysis for acute stroke, we included patients from June 2009 to January 2011.

Aim and design

The aims of the study are: to estimate the effect of remote ischemic perconditioning as adjunctive therapy to intravenous alteplase of acute ischemic stroke within the 4½-h time window and to investigate the feasibility of remote ischemic perconditioning performed during transport to hospital in patients displaying symptoms of acute stroke. Patients are randomized to remote ischemic perconditioning in a single-blinded fashion during transportation to hospital. Only patients with magnetic resonance imaging-proven ischemic stroke, who subsequently are treated with intravenous alteplase, and in selected cases additional endovascular treatment, are finally included in the study.

Study outcomes

Primary end-point is penumbral salvage. Penumbra is defined as hypoperfused yet viable tissue identified as the mismatch between perfusion-weighted imaging and diffusion-weighted imaging lesion on magnetic resonance imaging scans. Primary outcome is a mismatch volume not progressing to infarction on one-month follow-up T2 fluid attenuated inversion recovery. Secondary end-points include: infarct growth (expansion of the diffusion-weighted imaging lesion) from baseline to the 24-h and one-month follow-up examination. Infarct growth inside and outside the acute perfusion-weighted imaging–diffusion-weighted imaging mismatch zone is quantified by use of coregistration. Clinical outcome after three-months. The influence of physical activity (Physical Activity Scale for the Elderly score) on effect of remote ischemic perconditioning. Feasibility of remote ischemic perconditioning in acute stroke patients.

Summary

This phase 3 trial is the first study in patients with acute ischemic stroke to evaluate the effect size of remote ischemic perconditioning as a pretreatment to intravenous alteplase, measured as penumbral salvage on multimodal magnetic resonance imaging and clinical outcome after three-months follow-up.

Texture-based analysis of COPD: a data-driven approach

This study presents a fully automatic, data-driven approach for texture-based quantitative analysis of chronic obstructive pulmonary disease (COPD) in pulmonary computed tomography (CT) images. The approach uses supervised learning where the class labels are, in contrast to previous work, based on measured lung function instead of on manually annotated regions of interest (ROIs). A quantitative measure of COPD is obtained by fusing COPD probabilities computed in ROIs within the lung fields where the individual ROI probabilities are computed using a k nearest neighbor (kNN ) classifier. The distance between two ROIs in the kNN classifier is computed as the textural dissimilarity between the ROIs, where the ROI texture is described by histograms of filter responses from a multi-scale, rotation invariant Gaussian filter bank. The method was trained on 400 images from a lung cancer screening trial and subsequently applied to classify 200 independent images from the same screening trial. The texture-based measure was significantly better at discriminating between subjects with and without COPD than were the two most common quantitative measures of COPD in the literature, which are based on density. The proposed measure achieved an area under the receiver operating characteristic curve (AUC) of 0.713 whereas the best performing density measure achieved an AUC of 0.598. Further, the proposed measure is as reproducible as the density measures, and there were indications that it correlates better with lung function and is less influenced by inspiration level.

Dissimilarity-based classification of anatomical tree structures

A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment between the branch feature vectors representing those trees. Hereby, localized information in the branches is collectively used in classification and variations in feature values across the tree are taken into account. An approximate anatomical correspondence between matched branches can be achieved by including anatomical features in the branch feature vectors. The proposed approach is applied to classify airway trees in computed tomography images of subjects with and without chronic obstructive pulmonary disease (COPD). Using the wall area percentage (WA%), a common measure of airway abnormality in COPD, as well as anatomical features to characterize each branch, an area under the receiver operating characteristic curve of 0.912 is achieved. This is significantly better than computing the average WA%.

The expression and regulation of bone-acting cytokines in human peripheral adipose tissue in organ culture

The humoral cross-talk between bone and fat is an area of increasing interest. We investigated the expression and regulation of the bone-acting cytokines; bone morphogenetic protein 2 (BMP2), connective tissue growth factor (CTGF), osteoprotegerin (OPG), and transforming growth factor beta (TGFB1). Subcutaneous adipose tissue was aspirated from lean, healthy women. Tissue samples were incubated with interleukin 1-β (IL1-β), tumor necrosis factor-α (TNF-α), cortisol, troglitazone, IL1-β + troglitazone, or vehicle. Gene expression in the adipose tissue was analyzed using qPCR and protein levels in the incubation media were analyzed using ELISA. OPG expression and secretion was diminished by 40.8% and 43.1% respectively, by cortisol, and OPG expression was diminished by 67.5% by troglitazone (p<0.05). The proinflammatory cytokines IL1-β and TNF-α significantly increased the expression of CTGF (p<0.05) by 65.1% and 101.3%, respectively, and the expression and secretion of OGP by 62.3-165.8% (p<0.05). This interleukin 1-β mediated increase in CTGF- and OPG expression and secretion was ameliorated by troglitazone. Troglitazone and related drugs are known to have adverse effects on bone. We suggest that this could be mediated via altered cytokine production in adipose tissue. Moreover, obese individuals have a low-grade inflammation in their adipose tissue and have higher bone mineral density than lean individuals. We suggest that this inflammation may increase the expression and secretion of OPG and CTGF and thereby increase BMD. In conclusion, bone acting cytokines are produced in the adipose tissue and may affect bone through endocrine mechanisms.

Systemic thrombolytic therapy alone and in combination with mechanical revascularization in acute ischemic stroke in two children

Thrombolytic therapy is not recommended for acute ischemic stroke (AIS) in patients under the age of 18 and published experience is limited. In this case report, we describe two children treated with systemic thrombolytic therapy. One child received additional mechanical revascularization and achieved a good clinical outcome. The differences in the fibrinolytic system and the different etiology of AIS in childhood may limit a simple extrapolation of the adult guidelines for systemic thrombolytic therapy. Acute multimodal imaging to clarify the etiology of AIS might help to select the most appropriate treatment modality.

Localization of white-matter lesions and effect of vascular risk factors in late-onset major depression

BACKGROUND

Several studies suggest that patients with late-onset major depression (MD) have an increased load of cerebral white-matter lesions (WMLs) compared with age-matched controls. Vascular risk factors such as hypertension and smoking may confound such findings. Our aim was to investigate the association between the localization and load of WMLs in late-onset MD with respect to vascular risk factors.

METHOD

We examined 22 consecutive patients with late-onset first-episode MD and 22 age- and gender-matched controls using whole-brain magnetic resonance imaging (MRI). The localization, number and volume of WMLs were compared between patients and controls, while testing the effect of vascular risk factors.

RESULTS

Among subjects with one or more WMLs, patients displayed a significantly higher WML density in two white-matter tracts: the left superior longitudinal fasciculus and the right frontal projections of the corpus callosum. These tracts are part of circuitries essential for cognitive and emotional functions. Analyses revealed no significant difference in the total number and volume of WMLs between groups. Patients and controls showed no difference in vascular risk factors, except for smoking. Lesion load was highly correlated with smoking.

CONCLUSIONS

Our results indicate that lesion localization rather than lesion load differs between patients with late-onset MD and controls. Increased lesion density in regions associated with cognitive and emotional functions may be crucial in late-onset MD, and vascular risk factors such as smoking may play an important role in the pathophysiology of late-onset MD, consistent with the vascular depression hypothesis.

Quantitative analysis of pulmonary emphysema using local binary patterns

We aim at improving quantitative measures of emphysema in computed tomography (CT) images of the lungs. Current standard measures, such as the relative area of emphysema (RA), rely on a single intensity threshold on individual pixels, thus ignoring any interrelations between pixels. Texture analysis allows for a much richer representation that also takes the local structure around pixels into account. This paper presents a texture classification-based system for emphysema quantification in CT images. Measures of emphysema severity are obtained by fusing pixel posterior probabilities output by a classifier. Local binary patterns (LBP) are used as texture features, and joint LBP and intensity histograms are used for characterizing regions of interest (ROIs). Classification is then performed using a k nearest neighbor classifier with a histogram dissimilarity measure as distance. A 95.2% classification accuracy was achieved on a set of 168 manually annotated ROIs, comprising the three classes: normal tissue, centrilobular emphysema, and paraseptal emphysema. The measured emphysema severity was in good agreement with a pulmonary function test (PFT) achieving correlation coefficients of up to |r| = 0.79 in 39 subjects. The results were compared to RA and to a Gaussian filter bank, and the texture-based measures correlated significantly better with PFT than did RA.

Assessment of dementia in nursing home residents by nurses and assistants: criteria validity and determinants

OBJECTIVES

To describe the criterion validity of nursing home staff's assessment of organic disorder compared with ICD-10 criteria, and to identify determinants of staff assessment of organic disorder.

METHOD

Two hundred and eighty-eight residents were diagnosed using the GMS-AGECAT. Nursing staff members were interviewed about the residents' activities of Daily Living, behavioural problems, orientation in surroundings and communication skills, and asked if the resident had an organic disorder. Multiple logistic regression was used to select the items that most strongly determined staff assessment of organic disorder.

RESULTS

Sixty-two per cent of the residents were diagnosed by GMS-AGECAT as having organic disorder, 78% of these were correctly identified by the staff. Whether analysed among residents with or without organic disorder, or in the total group of residents, the staff assessment of the presence of organic disorder depended on a limited set of behavioural characteristics of the resident, namely 'going to the toilet in inappropriate places', 'saying things that do not make sense' and impairment in orientation.

CONCLUSIONS

Staff comprehension of organic disorder resulted in over- as well as under-labelling of residents, a tendency that will affect communication with medical personnel and may lead to inadequate or wrong medical treatment and to negative performance as well as negative role expectations in everyday life in nursing homes.

Determinants for the use of psychotropics among nursing home residents

PURPOSE

To characterise the prescription pattern of psychotropics in Danish nursing homes and to identify diagnostic, behavioural, cognitive and performance characteristics associated with prevalent psychotropic drug use.

METHODS

Prescribed daily medication was recorded from nurses' files. Based on the Anatomical Therapeutical Chemical (ATC) classification index, psychotropics were categorised into neuroleptics, benzodiazepines and antidepressants. Two hundred and eighty-eight residents were diagnosed using the GMS-AGECAT. One hundred and eighteen staff members were interviewed about the residents's Activities of Daily Living (ADL), behavioural problems (Nursing Home Behavior Problem Scale), orientation, communication skills and if the resident had any psychiatric disorder. Multiple logistic regression was used to select the items that determined the use of psychotropics.

RESULTS

Fifty-six percent of the residents received a psychotropic, 21% received neuroleptics, 38% received benzodiazepines and 24% received antidepressants. In the multivariate analysis, staff assessment of the resident's mental health was a determinant for the use of all types of specific psychotropics, whereas a GMS-AGECAT diagnosis only determined the use of neuroleptics. Behavioural problems were a determinant for the use of neuroleptics and the use of benzodiazepines irrespective of the psychiatric diagnosis of the resident. Use of antidepressants was associated with male gender and increasing age.

CONCLUSIONS

Staff perceptions of psychiatric morbidity and norms have a greater impact on the prescription of psychotropics than standardised clinical criteria.

Determinants for the use of psychotropics among nursing home residents

PURPOSE

To characterise the prescription pattern of psychotropics in Danish nursing homes and to identify diagnostic, behavioural, cognitive and performance characteristics associated with prevalent psychotropic drug use.

METHODS

Prescribed daily medication was recorded from nurses' files. Based on the Anatomical Therapeutical Chemical (ATC) classification index, psychotropics were categorised into neuroleptics, benzodiazepines and antidepressants. Two hundred and eighty-eight residents were diagnosed using the GMS-AGECAT. One hundred and eighteen staff members were interviewed about the residents's Activities of Daily Living (ADL), behavioural problems (Nursing Home Behavior Problem Scale), orientation, communication skills and if the resident had any psychiatric disorder. Multiple logistic regression was used to select the items that determined the use of psychotropics.

RESULTS

Fifty-six percent of the residents received a psychotropic, 21% received neuroleptics, 38% received benzodiazepines and 24% received antidepressants. In the multivariate analysis, staff assessment of the resident's mental health was a determinant for the use of all types of specific psychotropics, whereas a GMS-AGECAT diagnosis only determined the use of neuroleptics. Behavioural problems were a determinant for the use of neuroleptics and the use of benzodiazepines irrespective of the psychiatric diagnosis of the resident. Use of antidepressants was associated with male gender and increasing age.

CONCLUSIONS

Staff perceptions of psychiatric morbidity and norms have a greater impact on the prescription of psychotropics than standardised clinical criteria.